Pipe network leakage risk assessment method and system based on hydraulic model

By constructing a hydraulic-acoustic fusion model and combining multi-scale abnormal fluctuation spatiotemporal decoupling and fuzzy logic judgment, the problems of low efficiency and insufficient accuracy of traditional leakage detection methods are solved, and real-time and accurate management of pipeline leakage is realized.

CN120875531AInactive Publication Date: 2025-10-31WUXI YUNSONG INFORMATION TECH CO LTD
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Patent Information

Application Number
CN202510907350.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-07-02
Publication Date
2025-10-31
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

Technical Problem

Traditional leakage detection methods are inefficient and have a high false alarm rate, making it difficult to achieve real-time monitoring and accurate location. Hydraulic models and voiceprint recognition alone are insufficient to cope with complex pipe networks and environmental noise interference.

Method used

A hydraulic-acoustic fusion model is constructed. By decoupling the spatiotemporal components of multi-scale abnormal fluctuations and using fuzzy logic judgment, combined with real-time sensor data, dynamic matching is performed to screen the optimal anti-disturbance leakage suppression strategy, thereby achieving real-time quantification and accurate assessment of leakage risk.

Benefits of technology

It improves the accuracy and real-time performance of leak detection, reduces false alarms and missed alarms, enhances the automation and intelligence of pipeline network management, and optimizes resource utilization and repair efficiency.

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Abstract

The invention relates to the technical field of pipe network leakage risk assessment, in particular to a pipe network leakage risk assessment method and system based on a hydraulic model. The method comprises the following steps: acquiring urban pipe network structure data and urban pipe network sensing data, and constructing a pipe network hydraulic-voiceprint fusion model; performing multi-scale abnormal fluctuation space-time decoupling based on the pipe network hydraulic-voiceprint fusion model to obtain potential leakage structure data of the pipe network; predicting a pipe network leakage point influence range according to the pipe network potential leakage structure data, and performing fuzzy logic leakage probability judgment to obtain a leakage deduction report; acquiring real-time pipe network sensing data, and quantifying a risk level to obtain actual leakage risk level data of a pipe network node; screening leakage suppression strategies according to the actual leakage risk level data of the pipe network nodes; and real-time pipe network repair feedback data is obtained, health state evolution is carried out, and a leakage pipe network structure repair evaluation report is obtained. According to the invention, the accuracy and reliability of pipe network leakage detection can be improved.
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